Linear Algebra-Inspired Machine Learning with MATLAB
Overview
Linear algebra is a foundational course for science and engineering but, teaching foundational mathematics in the era of deep learning and large language models is becoming a challenge. In this talk, we will explore a modern application of linear algebra for machine learning that is meant to modernize the teaching of a fundamental course. A linear algebra inspired, digit recognition algorithm will be presented, based exclusively on linear algebra concepts studied in a first linear algebra class taken by STEM scientists and engineers. The overview of the algorithm will be followed by an interactive demo in MATLAB, that also allows the user to experiment with their own handwriting.
About the Presenter
Mike Michailidis is the mathematics academic discipline manager at MathWorks. He received his B.Sc. in Mathematics and M.Sc. in Applied Mathematics from the Aristotle University of Thessaloniki, Greece. He was awarded a Ph.D. in Electrical Engineering from the University of Denver, conducting research on modeling and control of unmanned aerial vehicles with time-varying aerodynamic uncertainties. After serving as a postdoc and adjunct professor at the University of Denver for a couple years, Mike has been on a mission to harmoniously bridge the worlds of mathematics and computation ever since.
Product Focus
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